Probabilistic & Bayesian Thinking

Core principle: Probabilistic thinking replaces vague confidence with calibrated estimates. Bayesian thinking updates those estimates as evidence arrives — neither clinging to priors nor overreacting to new data.

Core Concepts

Probability as Degree of Belief

"Will probably work" → 60%? 90%? Forcing a number exposes vague confidence and creates a baseline for updating.

Base Rates

Find the base rate before estimating a specific event — how often does this event type occur in a reference class?

"Will this feature succeed?" → What % of similar features in similar products succeeded?

Ignoring base rates (base rate fallacy) is a top reasoning error.